U.S. patent number 10,157,356 [Application Number 15/379,267] was granted by the patent office on 2018-12-18 for activity based resource allocation modeling.
This patent grant is currently assigned to Apptio, Inc.. The grantee listed for this patent is Apptio, Inc.. Invention is credited to Nikolas Charles Besagno, David Alexander Brokaw, Peter Whitney Goubert, Israel Hilerio, Mikalai Panasiuk, Su Shen.
United States Patent |
10,157,356 |
Hilerio , et al. |
December 18, 2018 |
Activity based resource allocation modeling
Abstract
Embodiments are directed to modeling resource allocations. A
data model may be provided to an activity modeling engine. The
activity modeling engine may be employed to provide an activity
model based on the data model, such that the activity model may
include activity objects that each may be associated with
bills-of-materials (BOMs). Resource allocations from source
activity objects to target activity objects may be provided based
on the BOMs, such that the resource allocations may be modeled
using unit values defined by the BOMs. A report visualizing the
activity model may be provided and presented on a hardware
display.
Inventors: |
Hilerio; Israel (Kenmore,
WA), Shen; Su (Seattle, WA), Goubert; Peter Whitney
(Seattle, WA), Besagno; Nikolas Charles (Bellevue, WA),
Brokaw; David Alexander (Woodinville, WA), Panasiuk;
Mikalai (Bellevue, WA) |
Applicant: |
Name |
City |
State |
Country |
Type |
Apptio, Inc. |
Bellevue |
WA |
US |
|
|
Assignee: |
Apptio, Inc. (Bellevue,
WA)
|
Family
ID: |
62489408 |
Appl.
No.: |
15/379,267 |
Filed: |
December 14, 2016 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20180165619 A1 |
Jun 14, 2018 |
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L
41/22 (20130101); G06Q 10/0875 (20130101); H04L
41/145 (20130101); G06Q 10/06315 (20130101); G06Q
10/067 (20130101) |
Current International
Class: |
G06Q
10/06 (20120101); H04L 12/24 (20060101) |
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2018, pp. 1-76. cited by applicant .
Official Communication for U.S. Appl. No. 13/935,147 dated Apr. 5,
2018, pp. 1-14. cited by applicant .
Official Communication for U.S. Appl. No. 14/867,552 dated May 31,
2018, pp. 1-22. cited by applicant.
|
Primary Examiner: Mansfield; Thomas L
Attorney, Agent or Firm: Branch; John W. Lowe Graham Jones
PLLC
Claims
What is claimed as new and desired to be protected by Letters
Patent of the United States is:
1. A method for modeling resource allocations using a network
computer that employs one or more processors to execute
instructions that perform actions, comprising: instantiating an
activity modeling engine that is provided a data model, wherein the
data model is comprised of two or more nodes and one or more edges
stored in a self-referential database in a memory of a computer
that is configured and arranged to store the data model, and
wherein the data model's data objects are stored in the database in
a single table that includes different records for different data
objects that include references to other different records for
other data objects, and wherein each node represents a model object
and each edge represents a resource allocation, and wherein the
self-referential database provides faster execution of a query of
the data model objects than a referential database that executes
the same query on the same data model objects more slowly because
it also executes database query join instructions; employing the
activity modeling engine to provide an activity model based on the
data model, wherein the activity model includes one or more
activity objects that each are associated with one or more
bills-of-materials (BOMs); providing one or more resource
allocations from one or more source activity objects to one or more
target activity objects based on the one or more BOMs, wherein the
one or more resource allocations are modeled using unit values or
allocation percentage shares defined by the one or more BOMs; and
providing a report visualizing the activity model, wherein the
report is presented by a hardware display, and wherein geolocation
information based on electronic signals processed by a Global
Positioning System (GPS) device is employed to improve one or more
users' understanding by modifying a visual presentation in a
display that includes one or more of a database, a user interface,
an internal process or the report visualizing the activity model
based on a location of each client computer employed by the one or
more users, wherein the modifications in the visual presentation
include one or more of time zone, currency, calendar format, or
language.
2. The method of claim 1, wherein providing the activity model
based on the data model, further comprises: traversing the data
model to identify one or more model objects included in the data
model; and providing the one or more activity objects for the
activity model based on the one or more identified model
objects.
3. The method of claim 1, further comprising, when one or more
modifications are made to the activity model, modifying the data
model based on the one or more modifications.
4. The method of claim 1, further comprising, when one or more
modifications are made to the data model, modifying the activity
model based on the one or more modifications.
5. The method of claim 1, wherein providing the activity model
based on the data model, further comprises, providing one or more
specialized activity objects that include one or more of a service
object, a project object, a department object, a labor pool object,
or a business unit object.
6. The method of claim 1, wherein modeling the one or more resource
allocations using unit values or allocation percentage shares
defined by the one or more BOMs, further comprises, using two or
more different unit values or different allocation percentage
shares that are associated with two or more of the one or more
activity objects.
7. A system for modeling resource allocations, comprising: a
network computer, comprising: a transceiver that communicates over
the network; a memory that stores at least instructions; and one or
more processor devices that execute instructions that perform
actions, including: instantiating an activity modeling engine that
is provided a data model, wherein the data model is comprised of
two or more nodes and one or more edges stored in a
self-referential database in a memory of a computer that is
configured and arranged to store the data model, and wherein the
data model's data objects are stored in the database in a single
table that includes different records for different data objects
that include references to other different records for other data
objects, and wherein each node represents a model object and each
edge represents a resource allocation, and wherein the
self-referential database provides faster execution of a query of
the data model objects than a referential database that executes
the same query on the same data model objects more slowly because
it also executes database query join instructions; employing the
activity modeling engine to provide an activity model based on the
data model, wherein the activity model includes one or more
activity objects that each are associated with one or more
bills-of-materials (BOMs); providing one or more resource
allocations from one or more source activity objects to one or more
target activity objects based on the one or more BOMs, wherein the
one or more resource allocations are modeled using unit values or
allocation percentage shares defined by the one or more BOMs; and
providing a report visualizing the activity model, wherein the
report is presented by a hardware display, and wherein geolocation
information based on electronic signals processed by a Global
Positioning System (GPS) device is employed to improve one or more
users' understanding by modifying a visual presentation in a
display that includes one or more of a database, a user interface,
an internal process or the report visualizing the activity model
based on a location of each client computer employed by the one or
more users, wherein the modifications in the visual presentation
include one or more of time zone, currency, calendar format, or
language; and a client computer, comprising: a client computer
transceiver that communicates over the network; a client computer
memory that stores at least instructions; and one or more processor
devices that execute instructions that perform actions, including:
displaying the report on another hardware display.
8. The system of claim 7, wherein providing the activity model
based on the data model, further comprises: traversing the data
model to identify one or more model objects included in the data
model; and providing the one or more activity objects for the
activity model based on the one or more identified model
objects.
9. The system of claim 7, wherein the one or more network computer
processor devices execute instructions that perform actions,
further comprising, when one or more modifications are made to the
activity model, modifying the data model based on the one or more
modifications.
10. The system of claim 7, wherein the one or more network computer
processor devices execute instructions that perform actions,
further comprising, when one or more modifications are made to the
data model, modifying the activity model based on the one or more
modifications.
11. The system of claim 7, wherein providing the activity model
based on the data model, further comprises, providing one or more
specialized activity objects that include one or more of a service
object, a project object, a department object, a labor pool object,
or a business unit object.
12. The system of claim 7, wherein modeling the one or more
resource allocations using unit values or allocation percentage
shares defined by the one or more BOMs, further comprises, using
two or more different unit values or different allocation
percentage shares that are associated with two or more of the one
or more activity objects.
13. A processor readable non-transitory storage media that includes
instructions for modeling resource allocations, wherein execution
of the instructions by one or more hardware processors performs
actions, comprising: instantiating an activity modeling engine that
is provided a data model, wherein the data model is comprised of
two or more nodes and one or more edges stored in a
self-referential database in a memory of a computer that is
configured and arranged to store the data model, and wherein the
data model's data objects are stored in the database in a single
table that includes different records for different data objects
that include references to other different records for other data
objects, and wherein each node represents a model object and each
edge represents a resource allocation, and wherein the
self-referential database provides faster execution of a query of
the data model objects than a referential database that executes
the same query on the same data model objects more slowly because
it also executes database query join instructions; employing the
activity modeling engine to provide an activity model based on the
data model, wherein the activity model includes one or more
activity objects that each are associated with one or more
bills-of-materials (BOMs); providing one or more resource
allocations from one or more source activity objects to one or more
target activity objects based on the one or more BOMs, wherein the
one or more resource allocations are modeled using unit values or
allocation percentage shares defined by the one or more BOMs; and
providing a report visualizing the activity model, wherein the
report is presented by a hardware display, and wherein geolocation
information based on electronic signals processed by a Global
Positioning System (GPS) device is employed to improve one or more
users' understanding by modifying a visual presentation in a
display that includes one or more of a database, a user interface,
an internal process or the report visualizing the activity model
based on a location of each client computer employed by the one or
more users, wherein the modifications in the visual presentation
include one or more of time zone, currency, calendar format, or
language.
14. The media of claim 13, wherein providing the activity model
based on the data model, further comprises: traversing the data
model to identify one or more model objects included in the data
model; and providing the one or more activity objects for the
activity model based on the one or more identified model
objects.
15. The media of claim 13, further comprising, when one or more
modifications are made to the activity model, modifying the data
model based on the one or more modifications.
16. The media of claim 13, further comprising, when one or more
modifications are made to the data model, modifying the activity
model based on the one or more modifications.
17. The media of claim 13, wherein providing the activity model
based on the data model, further comprises, providing one or more
specialized activity objects that include one or more of a service
object, a project object, a department object, a labor pool object,
or a business unit object.
18. The media of claim 13, wherein modeling the one or more
resource allocations using unit values or allocation percentage
shares defined by the one or more BOMs, further comprises, using
two or more different unit values or different allocation
percentage shares that are associated with two or more of the one
or more activity objects.
19. A network computer for modeling resource allocations,
comprising: a transceiver that communicates over the network; a
memory that stores at least instructions; and one or more processor
devices that execute instructions that perform actions, including:
instantiating an activity modeling engine that is provided a data
model wherein the data model is comprised of two or more nodes and
one or more edges stored in a self-referential database in a memory
of a computer that is configured and arranged to store the data
model, and wherein the data model's data objects are stored in the
database in a single table that includes different records for
different data objects that include references to other different
records for other data objects, and wherein each node represents a
model object and each edge represents a resource allocation, and
wherein the self-referential database provides faster execution of
a query of the data model objects than a referential database that
executes the same query on the same data model objects more slowly
because it also executes database query join instructions;
employing the activity modeling engine to provide an activity model
based on the data model, wherein the activity model includes one or
more activity objects that each are associated with one or more
bills-of-materials (BOMs); providing one or more resource
allocations from one or more source activity objects to one or more
target activity objects based on the one or more BOMs, wherein the
one or more resource allocations are modeled using unit values or
allocation percentage shares defined by the one or more BOMs; and
providing a report visualizing the activity model, wherein the
report is presented by a hardware display, and wherein geolocation
information based on electronic signals processed by a Global
Positioning System (GPS) device is employed to improve one or more
users' understanding by modifying a visual presentation in a
display that includes one or more of a database, a user interface,
an internal process or the report visualizing the activity model
based on a location of each client computer employed by the one or
more users, wherein the modifications in the visual presentation
include one or more of time zone, currency, calendar format, or
language.
20. The network computer of claim 19, wherein providing the
activity model based on the data model, further comprises:
traversing the data model to identify one or more model objects
included in the data model; and providing the one or more activity
objects for the activity model based on the one or more identified
model objects.
21. The network computer of claim 19, further comprising, when one
or more modifications are made to the activity model, modifying the
data model based on the one or more modifications.
22. The network computer of claim 19, further comprising, when one
or more modifications are made to the data model, modifying the
activity model based on the one or more modifications.
23. The network computer of claim 19, wherein providing the
activity model based on the data model, further comprises,
providing one or more specialized activity objects that include one
or more of a service object, a project object, a department object,
a labor pool object, or a business unit object.
24. The network computer of claim 19, wherein modeling the one or
more resource allocations using unit values or allocation
percentage shares defined by the one or more BOMs, further
comprises, using two or more different unit values or different
allocation percentage shares that are associated with two or more
of the one or more activity objects.
Description
TECHNICAL FIELD
The present invention relates generally to computer automated
resource allocation modeling, and more particularly, but not
exclusively to modeling resource allocation based on
activities.
BACKGROUND
Businesses that strive to remain viable and successful in today's
competitive commercial environment are required to adopt accurate
and responsive resource allocation and resource allocation planning
practices. Businesses may use models that apply modern budgeting,
forecasting and resource allocation techniques. For some resource
allocation techniques, the complexity of the underlying data models
may increase as the number of tracked activities and elements
increases. Therefore, for larger enterprises, sophisticated
computer programs and computers are often required to assist in
generating useful and relevant resource models for analyzing
resource allocations. In some cases, the large number of items and
entities required for enterprise scale resource modeling may make
development of resource models difficult. In some cases the
complexity of the models, the modelled items, and underlying
entities may require allocation planners to engage in a long drawn
out iterative process that may involve several stakeholders. In
some cases, businesses may attempt to reduce the complexities
associated with modeling individual resources by planning resource
allocation using collections of resources to represent various
business activities. Thus, it is with respect to these
considerations and others that the invention has been made.
BRIEF DESCRIPTION OF THE DRAWINGS
Non-limiting and non-exhaustive embodiments of the present
embodiments are described with reference to the following drawings.
In the drawings, like reference numerals refer to like parts
throughout the various figures unless otherwise specified. For a
better understanding of the present invention, reference will be
made to the following Detailed Description of the Various
Embodiments, which is to be read in association with the
accompanying drawings, wherein:
FIG. 1 shows components of one embodiment of an environment in
which at least one of the various embodiments may be practiced;
FIG. 2 shows one embodiment of a client computer that may include
many more or less components than those shown;
FIG. 3 shows one embodiment of a network computer that may be
included in a system implementing one or more embodiments of the
described innovations;
FIG. 4 illustrates a portion of a logical architecture for a data
model that may be enabled by at least one of the various
embodiments;
FIG. 5 illustrates an overview of a data model for providing total
resource allocation value for a business organization;
FIG. 6 shows a logical illustration of an activity model for
activity based resource allocation planning in accordance;
FIG. 7 shows a logical architecture of activity model components in
accordance with one or more embodiments;
FIG. 8 illustrates an overview flowchart for a process for activity
based resource allocation modeling in accordance with one or one
more of the various embodiments;
FIG. 9 illustrates an overview flowchart for a process for
providing an activity model for resource allocation modeling in
accordance with one or one more of the various embodiments;
FIG. 10 illustrates a flowchart for a process for modeling resource
allocation in accordance with one or one more of the various
embodiments;
FIG. 11 illustrates a flowchart for a process for providing
activity objects for resource allocation modeling in accordance
with one or one more of the various embodiments; and
FIG. 12 illustrates a flowchart for a process for using activity
based resource allocation modeling in accordance with one or one
more of the various embodiments.
DETAILED DESCRIPTION OF THE VARIOUS EMBODIMENTS
The present innovations now will be described more fully
hereinafter with reference to the accompanying drawings, which form
a part hereof, and which show, by way of illustration, specific
embodiments by which the invention may be practiced. This invention
may, however, be embodied in many different forms and should not be
construed as limited to the embodiments set forth herein; rather,
these embodiments are provided so that this disclosure will be
thorough and complete, and will fully convey the scope of the
invention to those skilled in the art. Among other things, the
present invention may be embodied as methods or devices.
Accordingly, the present invention may take the form of an entirely
hardware embodiment, an entirely software embodiment or an
embodiment combining software and hardware aspects. The following
detailed description is, therefore, not to be taken in a limiting
sense.
Throughout the specification and claims, the following terms take
the meanings explicitly associated herein, unless the context
clearly dictates otherwise. The phrase "In one of the embodiments"
or "in at least one of the various embodiments" as used herein does
not necessarily refer to the same embodiment, though it may.
Furthermore, the phrase "in another embodiment" as used herein does
not necessarily refer to a different embodiment, although it may.
Thus, as described below, various embodiments of the invention may
be readily combined, without departing from the scope or spirit of
the invention.
In addition, as used herein, the term "or" is an inclusive "or"
operator, and is equivalent to the term "and/or," unless the
context clearly dictates otherwise. The term "based on" is not
exclusive and allows for being based on additional factors not
described, unless the context clearly dictates otherwise. In
addition, throughout the specification, the meaning of "a," "an,"
and "the" include plural references. The meaning of "in" includes
"in" and "on."
As used herein, the terms "resource allocation model," and "data
model" refer to a graph based representation of a system of
resource allocation rules that may be used for tracking/analyzing
resource allocation, resource consumption, resource budgeting, or
the like. Nodes in the model may represent groups of items or
objects that may be associated with resources and/or resource
allocations. The edges of the graph may represent how resources may
be allocated between the nodes (objects). A data model may be a
visual rendering of a graph showing the nodes and the edges
connecting the nodes.
As used herein, the term "model line item," refers to a model line
item maps to resource being consumed. Model line item may be
associated with one or more line items in a data model and their
associated characteristics, including resources, costs,
description, or the like. For example, the costs associated with a
particular computer that is an email server may be represented by a
single model line item having a particular cost (e.g., the email
server may correspond to a model line item).
As used herein, the term "data object," or "model object" refers to
a set and/or class of model line items that may be grouped
together. Also, dataset information may be mapped to one or more
categories by a modeling engine. For example, a collection of
computers performing services such as email, web serving,
enterprise resource planning, may represent separate model line
items and they may be grouped into the Servers category and/or
Servers Object. Nodes in the data model graph may be considered to
represent model objects.
As used herein, the term "allocation rules" refer to rules in the
data model that determine how the resources from a model object are
apportioned between/among other model objects in the data model.
Also, such rules may be assigned to individual model line items.
For example, if an email server line item has a value of $1000 an
allocation rule may be defined such that 50% of the expense may be
allocated to the Marketing department and 50% may be allocated to
the Engineering department. Also, allocation rules may be applied
at the model objects as well as the model line item level.
As used herein, the term "assignment ratios," refers to the results
of applying one or more allocation rules and it is the distribution
ratio of resources to model line items or model objects. For
example, if $1000 may be allocated to Servers object, and the model
line item Email Server is allocated $800 and the model line item
FTP Server is allocated $200, the assignment ratios may be
determined to 80% to model line item Email Server and 20% to model
line item FTP Server. Assignment ratios may be explicitly defined
by allocation rules. Or, in some case, they may be derived from
allocation tables by converting the values into ratios of the total
allocation to the model object.
As used herein, the terms "activity model" refers to a graph based
representation of a system of activity based allocations that may
be used for tracking/analyzing resource allocation in terms of the
production and consumption of activities that correspond to the
resource allocation. Nodes in a activity model may represent
projects, services, departments, business units, or the like. The
edges of the graph may represent allocations showing how resources
may be transferred between the nodes (activity objects) in terms of
activities and/or items. An activity model may be displayed using a
visual rendering of a graph showing the nodes and the edges
connecting the nodes.
As used herein, the term "activity model object," or "activity
object" refer to data structures that represent activities included
in an activity model. Activities have some of the same type of
characteristics such as unique identifiers, names, costs, or the
like. Activity objects may be associated with one or more model
objects in a data model.
As used herein, the term "bill of materials (BOM)" refers to a data
structure representing a packaged resource or activity model that
may be consumed as an activity object by other BOMs. In this sense,
A BOM can be made up multiple BOMs because it can include one or
more activity objects. In some cases, activity objects may be
composed of other activity objects. BOMs define the constituent
sub-activities that may be required produce activity. For example,
an activity object representing onboarding a new employee may have
a BOM that includes, among other things, provisioning a computer,
provisioning a telephone, provisioning an email account, ten help
desk calls per year, and so on. In some cases, a BOM for a service
may be composed of other services which may have their own BOM.
As used herein, the term "external data source" refers to any
separately located system that may enable and/or provide access to
one or more datasets of information.
As used herein, the term "dataset" refers to a collection of data,
usually presented in tabular form. Each column may represent a
particular variable. Each row may represent a given member of the
dataset. Also, it may list values for fields for each of the
variables, such as name, location, cost, owner, manufacturer,
serial number, or the like. In some embodiments, datasets may be
ingested to produce data model objects for data models. Non-tabular
datasets can also take the form of marked up strings of characters,
such as an XML file.
As used herein, the term "source object" refers to a model object
in a data model that may be providing resource values that may be
allocated to one or more other model objects (target objects).
As used herein, the term "target object" refers to a model object
in a data model that may be allocated resources from one or more
other model objects (source objects).
As used herein, the term "source activity object" refers to an
activity object in an activity model that may be providing resource
values that may be allocated to one or more other activity objects
(target activity objects).
As used herein, the term "target activity object" refers to an
activity object in an activity model that may be allocated
resources from one or more other activity objects (source activity
objects).
The following briefly describes the embodiments of the invention in
order to provide a basic understanding of some aspects of the
invention. This brief description is not intended as an extensive
overview. It is not intended to identify key or critical elements,
or to delineate or otherwise narrow the scope. Its purpose is
merely to present some concepts in a simplified form as a prelude
to the more detailed description that is presented later.
Briefly stated embodiments are directed to modeling resource
allocations. In one or more of the various embodiments, a data
model may be provided to an activity modeling engine, such that the
data model may be comprised of two or more nodes and one or more
edges stored in a memory that is configured and arranged to store
the data model. And, such that each node represents a model object
and each edge represents a resource allocation.
In one or more of the various embodiments, the activity modeling
engine may be employed to provide an activity model based on the
data model, such that the activity model may include one or more
activity objects that each may be associated with one or more
bills-of-materials (BOMs). In one or more of the various
embodiments, providing the activity model may include traversing
the data model to identify one or more model objects included in
the data model. And, in some embodiments, providing the one or more
activity objects for the activity model based on the one or more
identified model objects.
In one or more of the various embodiments, providing the activity
model may include, providing one or more specialized activity
objects that include one or more of a service object, a project
object, a department object, a labor pool, a business unit object,
or the like.
In one or more of the various embodiments, one or more resource
allocations from one or more source activity objects to one or more
target activity objects may be provided based on the one or more
BOMs, such that the one or more resource allocations may be modeled
using unit values defined by the one or more BOMs. In one or more
of the various embodiments, modeling the one or more resource
allocations may include using two or more different unit values or
allocation percentage shares associated with two or more of the one
or more activity objects.
In one or more of the various embodiments, a report visualizing the
activity model, such that the report may be presented by a hardware
display.
In one or more of the various embodiments, if one or more
modifications are made to the activity model, the data model may be
updated based on the one or more modifications. In one or more of
the various embodiments, if one or more modifications are made to
the data model, the activity model may be updated based on the one
or more modifications.
Illustrated Operating Environment
FIG. 1 shows components of one embodiment of an environment in
which at least one of the various embodiments may be practiced. Not
all of the components may be required to practice various
embodiments, and variations in the arrangement and type of the
components may be made. As shown, system 100 of FIG. 1 includes
local area networks ("LANs")/wide area networks ("WANs")--(network)
111, wireless network 110, client computer 101-104, and Modeling
Platform Server 107.
Generally, client computers 102-104 may include virtually any
portable computing device capable of receiving and sending a
message over a network, such as network 111, wireless network 110,
or the like. Client computers 102-104 may also be described
generally as client computers that are configured to be portable.
Thus, client computers 102-104 may include virtually any portable
computing device capable of connecting to another computing device
and receiving information. Such devices include portable devices
such as, cellular telephones, smart phones, display pagers, radio
frequency (RF) devices, infrared (IR) devices, Personal Digital
Assistants (PDA's), handheld computers, laptop computers, wearable
computers, tablet computers, integrated devices combining one or
more of the preceding devices, or the like. As such, client
computers 102-104 typically range widely in terms of capabilities
and features. For example, a cell phone may have a numeric keypad
and a few lines of monochrome Liquid Crystal Display (LCD) on which
only text may be displayed. In another example, a web-enabled
mobile device may have a touch sensitive screen, a stylus, and
several lines of color LCD in which both text and graphics may be
displayed.
Client computer 101 may include virtually any computing device
capable of communicating over a network to send and receive
information, including messaging, performing various online
actions, or the like. The set of such devices may include devices
that typically connect using a wired or wireless communications
medium such as personal computers, tablet computers, multiprocessor
systems, microprocessor-based or programmable consumer electronics,
network Personal Computers (PCs), or the like. In at least one of
the various embodiments, at least some of client computers 102-104
may operate over wired and/or wireless network. Today, many of
these devices include a capability to access and/or otherwise
communicate over a network such as network 111 and/or wireless
network 110. Moreover, client computers 102-104 may access various
computing applications, including a browser, or other web-based
application.
In at least one of the various embodiments, one or more of client
computers 101-104 may be configured to operate within a business or
other entity to perform a variety of services for the business or
other entity. For example, client computers 101-104 may be
configured to operate as a web server, an accounting server, a
production server, an email server, video game server, an inventory
server, or the like. However, client computers 101-104 are not
constrained to these services and may also be employed, for
example, as an end-user computing node, in other embodiments.
Further, it should be recognized that more or less client computers
may be included within a system such as described herein, and
embodiments are therefore not constrained by the number or type of
client computers employed.
A web-enabled client computer may include a browser application
that is configured to receive and to send web pages, web-based
messages, or the like. The browser application may be configured to
receive and display graphics, text, multimedia, or the like,
employing virtually any web-based language, including a wireless
application protocol messages (WAP), or the like. In at least one
of the various embodiments, the browser application is enabled to
employ Handheld Device Markup Language (HDML), Wireless Markup
Language (WML), WMLScript, JavaScript, Standard Generalized Markup
Language (SGML), HyperText Markup Language (HTML), eXtensible
Markup Language (XML), HTML5, or the like, to display and send a
message. In at least one of the various embodiments, a user of the
client computer may employ the browser application to perform
various actions over a network.
Client computers 101-104 also may include at least one other client
application that is configured to receive and/or send data,
including resource allocation information, report requests (e.g.,
queries) between another computing device. Client applications may
include a capability to provide requests and/or receive data
relating to the data models, reports, project information,
allocation rules, or the like. The client application may provide
data representing assignment and/or allocation changes, selecting
templates, editing cost allocations between or among categories,
generating and/or modifying recursive allocation rules, or the
like. In at least one of the various embodiments, client
applications may receive and/or generate data related to data
models and may generate tables and relationships between and among
the data. In at least one of the various embodiments, client
computers 101-104 may view and/or modify generated data models.
Wireless network 110 is configured to couple client computers
102-104 and its components with network 111. Wireless network 110
may include any of a variety of wireless sub-networks that may
further overlay stand-alone ad-hoc networks, or the like, to
provide an infrastructure-oriented connection for client computers
102-104. Such sub-networks may include mesh networks, Wireless LAN
(WLAN) networks, cellular networks, or the like.
Wireless network 110 may further include an autonomous system of
terminals, gateways, routers, or the like connected by wireless
radio links, or the like. These connectors may be configured to
move freely and randomly and organize themselves arbitrarily, such
that the topology of wireless network 110 may change rapidly.
Wireless network 110 may further employ a plurality of access
technologies including 2nd (2G), 3rd (3G), 4th (4G), 5th (5G)
generation radio access for cellular systems, WLAN, Wireless Router
(WR) mesh, or the like. Access technologies such as 2G, 3G, 4G, 5G,
and future access networks may enable wide area coverage for mobile
devices, such as client computers 102-104 with various degrees of
mobility. For example, wireless network 110 may enable a radio
connection through a radio network access such as Global System for
Mobil communication (GSM), General Packet Radio Services (GPRS),
Enhanced Data GSM Environment (EDGE), Wideband Code Division
Multiple Access (WCDMA), High Speed Downlink Packet Access (HSDPA),
Long Term Evolution (LTE), or the like. In essence, wireless
network 110 may include virtually any wireless communication
mechanism by which information may travel between client computers
102-104 and another computing device, network, or the like.
Network 111 is configured to couple network computers with other
computing devices, including, modeling platform server computer
107, client computer(s) 101, and through wireless network 110 to
client computers 102-104. Network 111 is enabled to employ any form
of computer readable media for communicating information from one
electronic device to another. Also, network 111 can include the
Internet in addition to local area networks (LANs), wide area
networks (WANs), direct connections, such as through a universal
serial bus (USB) port, other forms of computer-readable media, or
any combination thereof. On an interconnected set of LANs,
including those based on differing architectures and protocols, a
router acts as a link between LANs, enabling messages to be sent
from one to another. In addition, communication links within LANs
typically include twisted wire pair or coaxial cable, while
communication links between networks may utilize analog telephone
lines, full or fractional dedicated digital lines including T1, T2,
T3, and T4, Integrated Services Digital Networks (ISDNs), Digital
Subscriber Lines (DSLs), wireless links including satellite links,
or other communications links known to those skilled in the art.
For example, various Internet Protocols (IP), Open Systems
Interconnection (OSI) architectures, and/or other communication
protocols, architectures, models, and/or standards, may also be
employed within network 111 and wireless network 110. Furthermore,
remote computers and other related electronic devices could be
remotely connected to either LANs or WANs via a modem and temporary
telephone link. In essence, network 111 includes any communication
method by which information may travel between computing
devices.
Additionally, communication media typically embodies
computer-readable instructions, data structures, program modules,
or other transport mechanism and includes any information delivery
media. By way of example, communication media includes wired media
such as twisted pair, coaxial cable, fiber optics, wave guides, and
other wired media and wireless media such as acoustic, RF,
infrared, and other wireless media. Such communication media is
distinct from, however, processor-readable storage devices
described in more detail below.
Modeling platform server computer 107 may include virtually any
network computer usable to perform data processing operation that
may be used for generating data models, allocation rules, recursive
allocation rules, resource allocations, displays and/or reports
thereof, such as network computer 300 of FIG. 3. In at least one of
the various embodiments, modeling platform server computer 107
employs various techniques to create, define, generate, automated
data processing applications for resource planning. Modeling
platform server computer 107 may include modules for generating
data processing applications that may provide and apply data models
that may include dataset templates, category templates, allocation
rules, recursive allocation rules or the like. Furthermore,
modeling platform server computer 107 may include and/or generate
data processing applications for visualizing the generated resource
allocations, data models, reciprocal models, allocation rules,
recursive allocation rules, or the like.
Devices that may operate as modeling platform server computer 107
include various network computers, including, but not limited to
personal computers, desktop computers, multiprocessor systems,
microprocessor-based or programmable consumer electronics, network
PCs, server devices, tablet computers, network appliances, or the
like. It should be noted that while modeling platform server
computer 107 is illustrated as a single network computer, the
invention is not so limited. Thus, in another embodiment, modeling
platform server computer 107 may represent a plurality of network
computers. For example, in at least one of the various embodiments,
modeling platform server computer 107 may be distributed over a
plurality of network computers and/or implemented using cloud
architecture.
Moreover, modeling platform server computer 107 is not limited to a
particular configuration. Rather, modeling platform server computer
107 may operate using a controller/worker approach over a plurality
of network computers, within a cluster, a peer-to-peer
architecture, cloud-based architecture (e.g., virtual machines),
and/or any of a variety of other architectures. Thus, modeling
platform server computer 107 is not to be construed as being
limited to a single environment, and other configurations, and
architectures are also envisaged. modeling platform server computer
107 may employ processes and architectures described below to
perform at least some of its actions.
Illustrative Client Computer
FIG. 2 shows one embodiment of client computer 200 that may include
many more or less components than those shown. Client computer 200
may represent, for example, at least one embodiment of mobile
computers or client computers shown in FIG. 1.
Client computer 200 may include processor 202 in communication with
memory 204 via bus 228. Client computer 200 may also include power
supply 230, network interface 232, audio interface 256, display
250, keypad 252, illuminator 254, video interface 242, input/output
interface 238, haptic interface 264, global positioning systems
(GPS) receiver 258, open air gesture interface 260, temperature
interface 262, camera(s) 240, projector 246, pointing device
interface 266, processor-readable stationary storage device 234,
and processor-readable removable storage device 236. Client
computer 200 may optionally communicate with a base station (not
shown), or directly with another computer. And in one embodiment,
although not shown, a gyroscope may be employed within client
computer 200 to measuring and/or maintaining an orientation of
client computer 200.
Power supply 230 may provide power to client computer 200. A
rechargeable or non-rechargeable battery may be used to provide
power. The power may also be provided by an external power source,
such as an AC adapter or a powered docking cradle that supplements
and/or recharges the battery.
Network interface 232 includes circuitry for coupling client
computer 200 to one or more networks, and is constructed for use
with one or more communication protocols and technologies
including, but not limited to, protocols and technologies that
implement any portion of the OSI model for mobile communication
(GSM), CDMA, time division multiple access (TDMA), UDP, TCP/IP,
SMS, MMS, GPRS, WAP, UWB, WiMax, SIP/RTP, GPRS, EDGE, WCDMA, LTE,
UMTS, OFDM, CDMA2000, EV-DO, HSDPA, or any of a variety of other
wireless communication protocols. Network interface 232 is
sometimes known as a transceiver, transceiving device, or network
interface card (NIC).
Audio interface 256 may be arranged to produce and receive audio
signals such as the sound of a human voice. For example, audio
interface 256 may be coupled to a speaker and microphone (not
shown) to enable telecommunication with others and/or generate an
audio acknowledgement for some action. A microphone in audio
interface 256 can also be used for input to or control of client
computer 200, e.g., using voice recognition, detecting touch based
on sound, and the like.
Display 250 may be a liquid crystal display (LCD), gas plasma,
electronic ink, light emitting diode (LED), Organic LED (OLED) or
any other type of light reflective or light transmissive display
that can be used with a computer. Display 250 may also include a
touch interface 244 arranged to receive input from an object such
as a stylus or a digit from a human hand, and may use resistive,
capacitive, surface acoustic wave (SAW), infrared, radar, or other
technologies to sense touch and/or gestures.
Projector 246 may be a remote handheld projector or an integrated
projector that is capable of projecting an image on a remote wall
or any other reflective object such as a remote screen.
Video interface 242 may be arranged to capture video images, such
as a still photo, a video segment, an infrared video, or the like.
For example, video interface 242 may be coupled to a digital video
camera, a web-camera, or the like. Video interface 242 may comprise
a lens, an image sensor, and other electronics. Image sensors may
include a complementary metal-oxide-semiconductor (CMOS) integrated
circuit, charge-coupled device (CCD), or any other integrated
circuit for sensing light.
Keypad 252 may comprise any input device arranged to receive input
from a user. For example, keypad 252 may include a push button
numeric dial, or a keyboard. Keypad 252 may also include command
buttons that are associated with selecting and sending images.
Illuminator 254 may provide a status indication and/or provide
light. Illuminator 254 may remain active for specific periods of
time or in response to events. For example, when illuminator 254 is
active, it may backlight the buttons on keypad 252 and stay on
while the client computer is powered. Also, illuminator 254 may
backlight these buttons in various patterns when particular actions
are performed, such as dialing another client computer. Illuminator
254 may also cause light sources positioned within a transparent or
translucent case of the client computer to illuminate in response
to actions.
Further, client computer 200 may also comprise hardware security
module (HSM) 268 for providing additional tamper resistant
safeguards for generating, storing and/or using
security/cryptographic information such as, keys, digital
certificates, passwords, passphrases, two-factor authentication
information, or the like. In some embodiments, hardware security
module may be employed to support one or more standard public key
infrastructures (PKI), and may be employed to generate, manage,
and/or store keys pairs, or the like. In some embodiments, HSM 268
may be arranged as a hardware card that may be added to a client
computer.
Client computer 200 may also comprise input/output interface 238
for communicating with external peripheral devices or other
computers such as other client computers and network computers. The
peripheral devices may include an audio headset, display screen
glasses, remote speaker system, remote speaker and microphone
system, and the like. Input/output interface 238 can utilize one or
more technologies, such as Universal Serial Bus (USB), Infrared,
WiFi, WiMax, Bluetooth.TM., and the like.
Haptic interface 264 may be arranged to provide tactile feedback to
a user of the client computer. For example, the haptic interface
264 may be employed to vibrate client computer 200 in a particular
way when another user of a computer is calling. Open air gesture
interface 260 may sense physical gestures of a user of client
computer 200, for example, by using single or stereo video cameras,
radar, a gyroscopic sensor inside a computer held or worn by the
user, or the like. Camera 240 may be used to track physical eye
movements of a user of client computer 200.
In at least one of the various embodiments, client computer 200 may
also include sensors 262 for determining geolocation information
(e.g., GPS), monitoring electrical power conditions (e.g., voltage
sensors, current sensors, frequency sensors, and so on), monitoring
weather (e.g., thermostats, barometers, anemometers, humidity
detectors, precipitation scales, or the like), light monitoring,
audio monitoring, motion sensors, or the like. Sensors 262 may be
one or more hardware sensors that collect and/or measure data that
is external to client computer 200
GPS transceiver 258 can determine the physical coordinates of
client computer 200 on the surface of the Earth, which typically
outputs a location as latitude and longitude values. GPS
transceiver 258 can also employ other geo-positioning mechanisms,
including, but not limited to, triangulation, assisted GPS (AGPS),
Enhanced Observed Time Difference (E-OTD), Cell Identifier (CI),
Service Area Identifier (SAI), Enhanced Timing Advance (ETA), Base
Station Subsystem (BSS), or the like, to further determine the
physical location of client computer 200 on the surface of the
Earth. It is understood that under different conditions, GPS
transceiver 258 can determine a physical location for client
computer 200. In at least one embodiment, however, client computer
200 may, through other components, provide other information that
may be employed to determine a physical location of the client
computer, including for example, a Media Access Control (MAC)
address, IP address, and the like.
In at least one of the various embodiments, applications, such as,
resource modeling client application 222, web browser 226, or the
like, may be arranged to employ geo-location information to select
one or more localization features, such as, time zones, languages,
currencies, calendar formatting, or the like. Localization features
may be used in user-interfaces, reports, as well as internal
processes and/or databases. In at least one of the various
embodiments, geo-location information used for selecting
localization information may be provided by GPS 258. Also, in some
embodiments, geolocation information may include information
provided using one or more geolocation protocols over the networks,
such as, wireless network 108 and/or network 111.
Human interface components can be peripheral devices that are
physically separate from client computer 200, allowing for remote
input and/or output to client computer 200. For example,
information routed as described here through human interface
components such as display 250 or keyboard 252 can instead be
routed through network interface 232 to appropriate human interface
components located remotely. Examples of human interface peripheral
components that may be remote include, but are not limited to,
audio devices, pointing devices, keypads, displays, cameras,
projectors, and the like. These peripheral components may
communicate over a Pico Network such as Bluetooth.TM., Zigbee.TM.
and the like. One non-limiting example of a client computer with
such peripheral human interface components is a wearable computer,
which might include a remote pico projector along with one or more
cameras that remotely communicate with a separately located client
computer to sense a user's gestures toward portions of an image
projected by the pico projector onto a reflected surface such as a
wall or the user's hand.
A client computer may include web browser application 226 that may
be configured to receive and to send web pages, web-based messages,
graphics, text, multimedia, and the like. The client computer's
browser application may employ virtually any programming language,
including a wireless application protocol messages (WAP), and the
like. In at least one embodiment, the browser application is
enabled to employ Handheld Device Markup Language (HDML), Wireless
Markup Language (WML), WMLScript, JavaScript, Standard Generalized
Markup Language (SGML), HyperText Markup Language (HTML),
eXtensible Markup Language (XML), HTML5, and the like.
Memory 204 may include RAM, ROM, and/or other types of memory.
Memory 204 illustrates an example of computer-readable storage
media (devices) for storage of information such as
computer-readable instructions, data structures, program modules or
other data. Memory 204 may store Unified Extensible Firmware
Interface (UEFI) 208 for controlling low-level operation of client
computer 200. The memory may also store operating system 206 for
controlling the operation of client computer 200. It will be
appreciated that this component may include a general-purpose
operating system such as a version of UNIX, or LINUX.TM., or a
specialized client computer communication operating system such as
Windows Phone.TM.. The operating system may include, or interface
with a Java and/or JavaScript virtual machine modules that enable
control of hardware components and/or operating system operations
via Java application programs or JavaScript programs.
Memory 204 may further include one or more data storage 210, which
can be utilized by client computer 200 to store, among other
things, applications 220 and/or other data. For example, data
storage 210 may also be employed to store information that
describes various capabilities of client computer 200. The
information may then be provided to another device or computer
based on any of a variety of events, including being sent as part
of a header during a communication, sent upon request, or the like.
Data storage 210 may also be employed to store social networking
information including address books, buddy lists, aliases, user
profile information, or the like. Data storage 210 may further
include program code, data, algorithms, and the like, for use by a
processor, such as processor 202 to execute and perform actions. In
one embodiment, at least some of data storage 210 might also be
stored on another component of client computer 200, including, but
not limited to, non-transitory processor-readable removable storage
device 236, processor-readable stationary storage device 234, or
even external to the client computer.
Applications 220 may include computer executable instructions
which, when executed by client computer 200, transmit, receive,
and/or otherwise process instructions and data. Applications 220
may include, for example, resource modeling client application 222.
In at least one of the various embodiments, resource modeling
client application 222 may be used to exchange communications to
and from modeling platform server computer 107, including, but not
limited to, queries, searches, API calls, configuration
information, reports, notifications, activity reports, allocation
planning information, or the like.
Other examples of application programs include calendars, search
programs, email client applications, IM applications, SMS
applications, Voice Over Internet Protocol (VOIP) applications,
contact managers, task managers, transcoders, database programs,
word processing programs, security applications, spreadsheet
programs, games, search programs, and so forth.
Additionally, in one or more embodiments (not shown in the
figures), client computer 200 may include one or more embedded
logic hardware devices instead of one or more CPUs, such as, an
Application Specific Integrated Circuits (ASICs), Field
Programmable Gate Arrays (FPGAs), Programmable Array Logic (PAL),
or the like, or combination thereof. The embedded logic hardware
devices may directly execute embedded logic to perform actions.
Also, in one or more embodiments (not shown in the figures), the
client computer may include one or more hardware microcontrollers
instead of one or more CPUs. In at least one embodiment, the
microcontrollers be system-on-a-chips (SOCs) that may directly
execute their own embedded logic to perform actions and access
their own internal memory and their own external Input and Output
Interfaces (e.g., hardware pins and/or wireless transceivers) to
perform actions.
Illustrative Network Computer
FIG. 3 shows one embodiment of network computer 300 that may be
included in a system implementing one or more embodiments of the
described innovations. Network computer 300 may include many more
or less components than those shown in FIG. 3. However, the
components shown are sufficient to disclose an illustrative
embodiment for practicing these innovations. Network computer 300
may represent, for example, one embodiment of modeling platform
server computer 107 of FIG. 1.
As shown in the figure, network computer 300 includes a processor
302 in communication with a memory 304 via a bus 328. Network
computer 300 also includes a power supply 330, network interface
332, audio interface 356, global positioning systems (GPS) receiver
362, display 350, keyboard 352, input/output interface 338,
processor-readable stationary storage device 334, and
processor-readable removable storage device 336. Power supply 330
provides power to network computer 300.
Network interface 332 includes circuitry for coupling network
computer 300 to one or more networks, and is constructed for use
with one or more communication protocols and technologies
including, but not limited to, protocols and technologies that
implement any portion of the Open Systems Interconnection model
(OSI model), global system for mobile communication (GSM), code
division multiple access (CDMA), time division multiple access
(TDMA), user datagram protocol (UDP), transmission control
protocol/Internet protocol (TCP/IP), Short Message Service (SMS),
Multimedia Messaging Service (MMS), general packet radio service
(GPRS), WAP, ultra wide band (UWB), IEEE 802.16 Worldwide
Interoperability for Microwave Access (WiMax), Session Initiation
Protocol/Real-time Transport Protocol (SIP/RTP), or any of a
variety of other wired and wireless communication protocols.
Network interface 332 is sometimes known as a transceiver,
transceiving device, or network interface card (NIC). Network
computer 300 may optionally communicate with a base station (not
shown), or directly with another computer.
Audio interface 356 is arranged to produce and receive audio
signals such as the sound of a human voice. For example, audio
interface 356 may be coupled to a speaker and microphone (not
shown) to enable telecommunication with others and/or generate an
audio acknowledgement for some action. A microphone in audio
interface 356 can also be used for input to or control of network
computer 300, for example, using voice recognition.
Display 350 may be a liquid crystal display (LCD), gas plasma,
electronic ink, light emitting diode (LED), Organic LED (OLED) or
any other type of light reflective or light transmissive display
that can be used with a computer. Display 350 may be a handheld
projector or pico projector capable of projecting an image on a
wall or other object.
Network computer 300 may also comprise input/output interface 338
for communicating with external devices or computers not shown in
FIG. 3. Input/output interface 338 can utilize one or more wired or
wireless communication technologies, such as USB.TM., Firewire.TM.,
WiFi, WiMax, Thunderbolt.TM., Infrared, Bluetooth.TM., Zigbee.TM.,
serial port, parallel port, and the like.
GPS transceiver 362 can determine the physical coordinates of
network computer 300 on the surface of the Earth, which typically
outputs a location as latitude and longitude values. GPS
transceiver 362 can also employ other geo-positioning mechanisms,
including, but not limited to, triangulation, assisted GPS (AGPS),
Enhanced Observed Time Difference (E-OTD), Cell Identifier (CI),
Service Area Identifier (SAI), Enhanced Timing Advance (ETA), Base
Station Subsystem (BSS), or the like, to further determine the
physical location of network computer 300 on the surface of the
Earth. It is understood that under different conditions, GPS
transceiver 362 can determine a physical location for network
computer 300.
Network computer 300 may also include sensors 364 for determining
geolocation information (e.g., GPS), monitoring electrical power
conditions (e.g., voltage sensors, current sensors, frequency
sensors, and so on), monitoring weather (e.g., thermostats,
barometers, anemometers, humidity detectors, precipitation scales,
or the like), light monitoring, audio monitoring, motion sensors,
or the like. Sensors 364 may be one or more hardware sensors that
collect and/or measure data that is external to network computer
300
In at least one embodiment, however, network computer 300 may,
through other components, provide other information that may be
employed to determine a physical location of the client computer,
including for example, a Media Access Control (MAC) address, IP
address, and the like.
Human interface components can be physically separate from network
computer 300, allowing for remote input and/or output to network
computer 300. For example, information routed as described here
through human interface components such as display 350 or keyboard
352 can instead be routed through the network interface 332 to
appropriate human interface components located elsewhere on the
network. Human interface components include any component that
allows the computer to take input from, or send output to, a human
user of a computer. Accordingly, pointing devices such as mice,
styluses, track balls, or the like, may communicate through
pointing device interface 358 to receive user input.
Memory 304 may include Random Access Memory (RAM), Read-Only Memory
(ROM), and/or other types of non-transitory computer readable
and/or writeable media. Memory 304 illustrates an example of
computer-readable storage media (devices) for storage of
information such as computer-readable instructions, data
structures, program modules or other data. Memory 304 stores a
basic input/output system (BIOS) 308 for controlling low-level
operation of network computer 300. The memory also stores an
operating system 306 for controlling the operation of network
computer 300. It will be appreciated that this component may
include a general-purpose operating system such as a version of
UNIX, or LINUX.TM., or a specialized operating system such as
Microsoft Corporation's Windows.RTM. operating system, or the Apple
Corporation's IOS.RTM. operating system. The operating system may
include, or interface with a Java virtual machine module that
enables control of hardware components and/or operating system
operations via Java application programs. Likewise, other runtime
environments may be included.
Memory 304 may further include one or more data storage 310, which
can be utilized by network computer 300 to store, among other
things, applications 320 and/or other data. For example, data
storage 310 may also be employed to store information that
describes various capabilities of network computer 300. The
information may then be provided to another device or computer
based on any of a variety of events, including being sent as part
of a header during a communication, sent upon request, or the like.
Data storage 410 may also be employed to store social networking
information including address books, buddy lists, aliases, user
profile information, or the like. Data storage 310 may further
include program code, data, algorithms, and the like, for use by a
processor, such as processor 302 to execute and perform actions
such as those actions described below. In one embodiment, at least
some of data storage 310 might also be stored on another component
of network computer 300, including, but not limited to,
non-transitory media inside processor-readable removable storage
device 336, processor-readable stationary storage device 334, or
any other computer-readable storage device within network computer
300, or even external to network computer 300. Data storage 310 may
include, for example, data model information 314, activity model
information 316, or the like.
Applications 320 may include computer executable instructions
which, when executed by network computer 300, transmit, receive,
and/or otherwise process messages (e.g., SMS, Multimedia Messaging
Service (MMS), Instant Message (IM), email, and/or other messages),
audio, video, and enable telecommunication with another user of
another mobile computer. Other examples of application programs
include calendars, search programs, email client applications, IM
applications, SMS applications, Voice Over Internet Protocol (VOIP)
applications, contact managers, task managers, transcoders,
database programs, word processing programs, security applications,
spreadsheet programs, games, search programs, and so forth.
Applications 320 may include resource modeling engine 322, activity
engine 324, visualization engine 325, analysis engine 326, other
applications 327, or the like, that may perform actions further
described below. In at least one of the various embodiments, one or
more of the applications may be implemented as modules and/or
components of another application. Further, in at least one of the
various embodiments, applications may be implemented as operating
system extensions, modules, plugins, or the like.
In at least one of the various embodiments, applications, such as,
resource modeling engine 322, activity engine 324, visualization
engine 325, analysis engine 326, other applications 327, or the
like, may be arranged to employ geo-location information to select
one or more localization features, such as, time zones, languages,
currencies, calendar formatting, or the like. Localization features
may be used in user-interfaces, reports, as well as internal
processes and/or databases. In at least one of the various
embodiments, geo-location information used for selecting
localization information may be provided by GPS 362. Also, in some
embodiments, geolocation information may include information
provided using one or more geolocation protocols over the networks,
such as, wireless network 108 and/or network 111.
Furthermore, in at least one of the various embodiments, resource
modeling engine 322, activity engine 324, visualization engine 325,
or analysis engine 326 may be operative in a cloud-based computing
environment. In at least one of the various embodiments, these
engines, and others, that comprise the modeling platform that may
be executing within virtual machines and/or virtual servers that
may be managed in a cloud-based based computing environment. In at
least one of the various embodiments, in this context applications
including the engines may flow from one physical network computer
within the cloud-based environment to another depending on
performance and scaling considerations automatically managed by the
cloud computing environment. Likewise, in at least one of the
various embodiments, virtual machines and/or virtual servers
dedicated to resource modeling engine 322, activity engine 324,
visualization engine 325, or analysis engine 326 may be provisioned
and de-commissioned automatically.
Further, in some embodiments, network computer 300 may also include
hardware security module (HSM) 360 for providing additional tamper
resistant safeguards for generating, storing and/or using
security/cryptographic information such as, keys, digital
certificates, passwords, passphrases, two-factor authentication
information, or the like. In some embodiments, hardware security
module may be employ to support one or more standard public key
infrastructures (PKI), and may be employed to generate, manage,
and/or store keys pairs, or the like. In some embodiments, HSM 360
may be arranged as a hardware card that may be installed in a
network computer.
Additionally, in one or more embodiments (not shown in the
figures), network computer 300 may include an one or more embedded
logic hardware devices instead of one or more CPUs, such as,
Application Specific Integrated Circuits (ASICs), Field
Programmable Gate Arrays (FPGAs), Programmable Array Logic (PALs),
or the like, or combination thereof. The one or more embedded logic
hardware devices may directly execute its embedded logic to perform
actions. Also, in one or more embodiments (not shown in the
figures), the network computer may include one or more hardware
microcontrollers instead of one or more CPUs. In at least one
embodiment, the one or more microcontrollers may directly execute
embedded logic to perform actions and access their own internal
memory and their own external Input and Output Interfaces (e.g.,
hardware pins and/or wireless transceivers) to perform actions.
E.g., they may be arranged as Systems On Chips (SOCs).
In at least one of the various embodiments, resource modeling
engine 322, activity engine 324, visualization engine 325, or
analysis engine 326 may enable a user to generate project plans,
allocation rules, data models, reports, what-if-analysis, or the
like. Also in at least one of the various embodiments, resource
modeling engine 322, activity engine 324, visualization engine 325,
or analysis engine 326 may employ processes, or parts of processes,
similar to those described below.
Illustrative Logical System Architecture
FIG. 4 illustrates a portion of a logical architecture for data
model 400 that may be enabled by at least one of the various
embodiments.
In at least one of the various embodiments, model 400 may have five
objects: GL 402, Servers 404, Storage 410, Support 414, and
Business Units 420. In at least one of the various embodiments,
each object contains a set of resource cost line items. For
example, GL 402 includes resource cost line items for Payroll,
Taxes and Rent. Likewise, Support 414 includes resource cost line
items Email, Printers, Telephone, and Parking. In at least one of
the various embodiments, each resource cost line item has one or
more associated resource values. For example, Storage 410 has two
resource cost line items, D1, and D2 (e.g., disk drives) having
associated resource cost values of $1000 each.
Allocation rules may be used to connect objects of data model 400.
In at least one of the various embodiments, allocation rules may
show how resources flow between the objects modeled by data model
400. Resulting in a graph where the objects may be represented as
nodes and the allocation rules may be represented as edges. In at
least one of the various embodiments, generally a data model may be
represented by a directed acyclic graph but that is not a
requirement for an operative model. In at least one of the various
embodiments, a model graph may contain cycles that are resolved or
estimated using mathematical techniques, including but not limited
to Gaussian elimination, Cholesky decomposition or Newton's
method.
In at least one of the various embodiments, data models may be
arranged to be stored in self-referential database such that some
or all of the data objects for a data model may be stored in the
same table. Accordingly, different records in the table may be
arranged to include references to other records in the same table
that also represent data model objects for a data model.
Accordingly, in some embodiments, the graph structure of a data
model may be represented in a single table rather than require
normalized databased tables. Accordingly, in some embodiments, the
data models may be traversed by scanning through a single table
rather than having to execute slower performing database query
joins, or the like.
In at least one of the various embodiments, allocation rule 406
represents a rule allocating 20% of the resources of object GL 402
(source object) to Servers object 404 (target object). In this
example, GL 402 includes resources values at $20,000, thus 20% of
$20,000 (e.g., $4,000) flows based on allocation rule 406 to
Servers 404. Likewise, allocation rule 408 may allocate $2,000 from
GL 402 to Storage 410. The other allocation rules in data model 400
allocate 100% of the resource to the next data object: allocation
rule 412 directs 100% of the resources (e.g., $4,000) to flow to
Support 414; allocation rule 418 directs 100% of the resources in
Support (e.g., $4,000) to flow to Business Units 420; and
allocation rule 416 directs 100% of the resources from Storage 410
to flow to Business Units 420.
In at least one of the various embodiments, resources that flows
into a data object may be allocated among the included resource
cost line items. In at least one of the various embodiments, each
object may have one or more rules that may describe the assignment
ratios for how the resources associate with a data object may be
assigned to resource cost line items. For the categories 404, 410,
414, and 420, simple allocation rules assign the resources in the
object evenly among the resource cost line items comprising each
data object. GL 402 may have different assignment ratios, in this
non-limiting example, the assignment ratio between the resource
cost line items may be 50% to Payroll, 25% to Taxes, and 25% to
Rent.
In at least one of the various embodiments, an assignment ratio may
represent how the resources in an organization may be assigned to
the actual resource cost line items. In at least one of the various
embodiments, rules may be applied that distribute the resources
based on formulas that may be defined by the users or
administrators who designed the data model. In at least one of the
various embodiments, the assignment ratios and allocations may be
modified as part of the modeling process.
The data model 400 is a simplified model useful for facilitating
discussion and understanding of the embodiments, since allocation
rules for models of large organizations can be numerous and
complex. However, model 400 is at least sufficient to enable one of
ordinary skill in the art to practice what is claimed herein.
FIG. 5 illustrates an overview of data model 500 for providing
total resource allocation value 502 for a system, such as a
business organization. Data source 506 provides a dataset to fields
of dataset template 508. At least some of the fields of dataset
template 508 normalize the provided dataset. Model template 504 is
arranged to map the normalized data in the fields of dataset
template 508 to a plurality of data object, including data objects
510, 512, 514, 516, 518, 522, 524, and 526. Also, although not
shown, each object may be associated with one or more allocation
rules so that allocated percentages of the normalized data set are
distributed to the plurality of data objects based on their
associated allocation rules.
Additionally, some of the objects may be aggregated into other data
objects. For example, objects 510 and 512 may be aggregated into
summing object 522. Also, as shown, objects 514 and 516 and 518 may
be aggregated together at block 520 and then further allocated to
summing object 524. Further, as shown, some portion of the
normalized dataset may be allocated directly to summing object 526.
The summing objects may then be allocated by allocation rules to
provide total resource allocation value 502.
Furthermore, although not shown, in at least one of the various
embodiments, data model 500 may be edited to include additional
analysis, such as recommendations, simulations, benchmarks, or the
like. For example, historical information from other models and
heuristics used by other anonymous systems using the same resource
may be employed at least in part to analyze and compare the current
model and suggest changes to that model that may be less costly in
providing a total resource value for the current system.
FIG. 6 shows a logical illustration of activity model 600 for
activity based resource allocation planning in accordance. In one
or more of the various embodiments, activity models, such as
activity model 600 may be used for planning resource allocation. In
one or more of the various embodiments, activity models may be
arranged to represent resource allocation in terms of the actual
activities being performed rather than a common resource allocation
unit.
In this example, activity model 600 is presented to provide a
framework for discussing the various features and/or embodiments
for activity based planning. In this example, activity model 600 is
a simplified representation that models the activity objects
associated with employees for an organization. In this example,
activity model 600 represents portions of an organization that has
500 employees, where each employee needs an email account and a
laptop computer.
In one or more of the various embodiments, activity model 600
includes one or more activity objects, such as, activity object 602
(email service), activity object 604 (human resources business
unit), activity object 606 (sales business unit), activity object
608 (helpdesk call center), activity object 610 (IT department).
These activity objects represent the active participants in this
limited model. In some embodiments, activity objects may be
classified into services, projects, business units, departments, or
the like. In this example, activity object 602 (email) is a
service; activity object 604 (human resources) is a business unit;
activity object 606 (sales) is a business unit; activity object 608
(helpdesk) is a department; and activity object 610 (IT) is a
department.
In one or more of the various embodiments, the edges shown in
activity model 600 represent resource allocations that occur
between its activity objects.
In this example, edge 616 represents laptops being provided from
activity object 610 to activity object 606; edge 622 represents
laptops being provided from activity object 610 to activity object
604; edge 624 represents laptops being provided from activity
object 610 to activity object 608; edge 616 represents laptops
being provided from activity object 610 to activity object 606;
edge 626 represents laptops being provided from activity object 610
to activity object 602; edge 612 represents email accounts being
provided from activity object 602 to activity object 606; edge 614
represents email accounts being provided from activity object 602
to activity object 604; edge 618 represents email accounts being
provided from activity object 602 to activity object 610; edge 620
represents email accounts being provided from activity object 602
to activity object 608; edge 624 represents laptops being provided
from activity object 610 to activity object 608; edge 622
represents laptops being provided from activity object 610 to
activity object 604; and edge 628 represents helpdesk calls being
provided from activity object 608 to activity object 602.
In one or more of the various embodiments, the edges of activity
model 600 represent resource allocation in terms of the activity
and/or services being produced and/or consumed. For example, edge
616 (among others) represent the number of laptops being provided
to an activity object. In this case, one laptop per employee
associated with activity object 606 (sales). Likewise, activity
object 602 produces email accounts, one per employee in this
example.
Accordingly, table 630 may be a data structure that represents the
specific allocations for a modeled organization. In some
embodiments, table 630 may include one or more columns, such as,
column 632 representing activity object identifiers (in this
example a name); column 634 represent the type of the activity
object; column 636 representing the resources produced by the
activity object; and column 638 representing resources consumed by
the activity object.
Accordingly, for this example, row 640 shows that the human
resources business unit (activity object 604) consumes 100 laptop
computers and 100 email accounts (reflecting that there are 100
employees in the human resources business unit); row 642 shows that
the sales business unit (activity object 606) consumes 200 laptop
computers and 200 email accounts (reflecting that there are 200
employees in the sales business unit); row 644 shows that the
helpdesk call center department (activity object 608) produces 1000
support calls and consumes 100 laptop computers and 100 email
accounts (reflecting that there are 100 employees in the helpdesk
department); row 646 shows that the IT department (activity object
610) produces 500 laptop computers and consumes 100 laptop
computers and 100 email accounts (reflecting that there are 100
employees in the IT department); and row 648 shows that the email
service (activity object 602) produces 500 email accounts and
consumes 1000 helpdesk support calls.
Accordingly, in one or more of the various embodiments, a user may
employ activity models, such as activity model 600 for planning
resource allocations and/or resource needs based on planned
activities. Thus, if one laptop computer is provided for each
employee, IT (activity object 610) plans for one laptop per
employee and allocates them accordingly. In contrast, a data model,
such as data model 500 may be arranged to represent the resource
allocation in terms of the costs of the underlying resource. While
representing the resource allocation in terms of its costs may be
an accurate representation, it may be harder to convey the nature
and/or necessity of the underlying activity.
For example, in some embodiments, a data model may include the same
allocation information just represented in different unit of
measure. A data model may be arranged to show that the IT
department is allocated $500,0000 and that it allocates $500,000 to
different consumers (representing $1000 per laptop computer).
Alternatively, if activity model 600 is used, it is clear that the
IT department is using the $500,000 for laptops that are allocated
to employees.
Thus, in this example, an activity model, such as activity model
600 may empower stakeholders in the IT department to clearly defend
and/or advocate for the resources they need. If a 5% cut is planned
using a data model, it is easy to just reduce the money allocation
to the IT department to $475,000. The allocation change may
seamlessly flow through the data model. However, if an activity
model is used, it may be easy to see that now the IT department can
only provide 475 laptops which results in 25 employees without
laptops computers.
Further, in one or more of the various embodiments, activity models
may include resource allocations that exceed the capacity of one or
more source objects. For example, an activity model may show that a
sales object is requesting more email accounts than the email
service can provide, and so on. Accordingly, in some embodiments,
the activity model could indicate deficiencies or shortfalls in
"down-line" resources that may not otherwise be easily predicted or
observed.
Likewise, in one or more of the various embodiments, activity
models may model systems where resources or capacities of one or
more activity objects may be un-used or un-allocated. For example,
an activity model may represent that an IT department may be
allocating 500 laptops even though the IT department has the
capacity to provide 600 laptops.
FIG. 7 shows a logical architecture of activity model components
700 in accordance with one or more embodiments. In one or more of
the various embodiments, activity models may be comprised of
activity objects and allocation line items. In one or more of the
various embodiments, activity object 702 may be a data structure
arranged to represent characteristics and/or attributes that may be
common to different types of activity objects. In some embodiments,
common characteristics and/or attributes may include object names,
object type identifiers, allocated resources, owner, or the
like.
In one or more of the various embodiments, specialized activity
object may be arranged to represent particular types of activities
and/or actors of an organization. In some embodiments, specialized
activity objects may include, projects object 704, services object
706, departments object 708, labor pools 710, business units object
712, or the like. In one or more of the various embodiments,
specialized activity objects may be arranged to include
characteristics and/or attributes unique to a given type of
activity object.
In one or more of the various embodiments, specialized activity
objects may include one or more bill-of-materials (BOM) that define
the sub-activities/sub-parts for a specialized activity. For
example, an email service activity object the provides email access
to employees may include a BOM that requires/includes 10 helpdesk
calls and 1 GB of storage per email for each provided email
account. In this example, if an organization plans to hire 100 new
employees and provide them email accounts, the activity model would
indicate that this plan consumes 1000 helpdesk calls and 100 GB of
data storage.
In another example, in one or more of the various embodiments, a
specialized activity object, such as an "on-board new employee
service" may be defined such that it includes a BOM that requires
one email account from the email service, one laptop computer
produced from the IT department, and so on. Thus, continuing with
this example, an activity model would clearly show that a plan to
hire 100 employees would require 100 laptops, 100 email accounts,
100 GB of storage, and capacity for 1000 helpdesk calls.
In one or more of the various embodiments, resource allocations may
be represented using a data structure such as line item 714.
Similar to activity objects and specialized activity objects, line
items may be specialized using data structures such as allocations
item 716, contracts item 718, or the like.
In one or more of the various embodiments, line item records may
represent actual resource allocations of activities in an activity
model. For example, the allocation of 100 laptops from the IT
department activity object to a sales activity object may be
represented by an allocation item.
Generalized Operations
FIGS. 8-12 represent the generalized operations for models for
visualizing resource allocation in accordance with at least one of
the various embodiments. In at least one of the various
embodiments, processes 800, 900, 1000, 1100, and 1200 described in
conjunction with FIGS. 8-12 may be implemented by and/or executed
on a single network computer, such as network computer 300 of FIG.
3. In other embodiments, these processes or portions thereof may be
implemented by and/or executed on a plurality of network computers,
such as network computer 300 of FIG. 3. However, embodiments are
not so limited, and various combinations of network computers,
client computers, virtual machines, or the like may be utilized.
Further, in at least one of the various embodiments, the processes
described in conjunction with FIGS. 8-12 may be operative in
activity based resource allocation modeling such as described in
conjunction with FIGS. 4-7.
FIG. 8 illustrates an overview flowchart for process 800 for
activity based resource allocation modeling in accordance with one
or one more of the various embodiments. After a start block, at
block 802, in at least one of the various embodiments, a data model
that models resource allocation for an organization may be provided
to an activity modeling engine, such as activity modeling engine
324.
At block 804, in one or more of the various embodiments, an
activity model may be provided based on the data model. In some
embodiments, one or more activity models may be provided based on
the information associated with data model. In one or more of the
various embodiments, the activity modeling engine may be arranged
to traverse the data model identifying one or more model objects
that may be mapped to one or more activity objects.
In one or more of the various embodiments, one or more activity
objects may be unassociated with specific model objects. For
example, an activity model may be arranged to include an email
service activity object that is not directly included in the data
model.
At block 806, in one or more of the various embodiments, the
activity model may be used to model the resource allocation for the
organization. Resource allocations in the activity model may be
defined in terms of units and/or values that may be relevant to the
source activity objects. In some embodiments, the users responsible
for an activity object (e.g., IT managers may be responsible for
the IT department object) may be enabled to define/select the
units/values that represent the allocation of the their resources.
For example, the IT department object may be arranged to allocate
resources such as laptop computers in terms of the number of units
provided rather than their monetary value.
Likewise, in one or more of the various embodiments, resources
allocations may be defined in terms of percentage shares, or the
like, rather than being limited to specific units or items. For
example, an marketing activity object may be defined to allocation
20% of its activities to one business unit and 80% to another.
Thus, the actual resource value or unit allocation to the two
business units in this example may vary depending on the capacity
of the marketing object.
At block 808, in one or more of the various embodiments, reports
may be provided based on the activity model and the modeled
resource allocations. In one or more of the various embodiments,
reports may include one or more interactive graphical displays of
allocation information provided using a visualization engine, such
as visualization engine 325.
At block 810, in one or more of the various embodiments,
optionally, during the resource modeling process, the activity
model may be modified to reflect updated plans and/or new
information. Accordingly, in one or more of the various
embodiments, activity modeling engine may be arranged to push
modifications made to the activity model to the underlying data
model. For example, if an activity model is modified to show that
an additional one hundred laptop computers are allocated from the
IT department to the sales business unit, the corresponding data
objects in the data model may be adjusted accordingly (e.g.,
showing that an additional $100,000 of IT's budget may be allocated
to the sales business unit data object).
This block is indicated as optional because in some cases the
activity model may remain unmodified. Also, in some embodiments,
the activity modeling engine may be configured to refrain from
automatically pushing modifications to the data model.
Next, control may be returned to a calling process.
FIG. 9 illustrates an overview flowchart for process 900 for
providing an activity model for resource allocation modeling in
accordance with one or one more of the various embodiments. After a
start block, at block 902, in at least one of the various
embodiments, a source activity object and a target activity object
may be provided. In one or more of the various embodiments, source
activity objects may be activity objects included in activity
models that allocate one or more resources to other activity
objects in the same activity models. Likewise, target activity
objects may be activity objects included in activity models that
may be allocated resources from other activity objects in the same
activity models.
In one or more of the various embodiments, one or more source
activity objects and/or one or more target activity objects may be
derived from one or more model objects included in one or more
underlying data models. Accordingly, in some embodiments, the
activity modeling engine may be arranged to traverse one or more
underlying data model to produce an activity model. Also, in one or
more of the various embodiments, a user may modify existing
(including automatically generated activity models) by adding,
removing, or modifying activity objects.
At block 904, In one or more of the various embodiments, allocation
information for allocation of resources from the source activity
object to the target activity object may be provided. In one or
more of the various embodiments, allocation information associated
with the data model may be processed to provide the resource
allocations for the activity model.
In one or more of the various embodiments, one or more rules
associated with bills-of-material (BOMs) included in the activity
objects may be executed to map resource allocations in the data
model to activity based resource allocations included in the
activity model. In one or more of the various embodiments, the
rules may include conversion formulas for mapping allocation values
from the data model to the activity model.
In one or more of the various embodiments, users may provide
resource allocation information that may be not included in the
data model. Likewise, allocation information may be provided from
one or more internal or external sources separate from the data
model.
In one or more of the various embodiments, each resource allocation
represented in an activity model may be defined against single
resources. Also, in one or more of the various embodiments,
resource allocations may be made against one or more resources
represented by a single activity object.
At block 906, in one or more of the various embodiments, one or
more reports may be provided the regarding the activity based
resource allocations. In one or more of the various embodiments,
the activity model may be provided to a visualization engine that
may traverse the activity model and render an interactive display
of the activity model for display on a hardware display. Next,
control may be returned to a calling process.
FIG. 10 illustrates a flowchart for process 1000 for modeling
resource allocation in accordance with one or one more of the
various embodiments. After a start block, at block 1002, in one or
more of the various embodiments, one or activities may be allocated
from a source activity object to a target activity object.
At block 1002, in one or more of the various embodiments, a
bill-of-material (BOM) corresponding to the allocated activity may
be provided. In one or more of the various embodiments, the source
activity object may be a specialized activity object that is
associated with one or more BOMs. Accordingly, in one or more of
the various embodiments, the resources, other activity objects, or
the like, for accomplishing the activity allocation may be defined
in one or more BOMs.
In one or more of the various embodiments, the BOM may be arranged
to include one or more rules that describe resources associated
with the allocated activities. For example, a BOM for a new email
address may have rules that require 1 GB of storage and 10 helpdesk
calls per year be consumed for each email account provided. BOM
rules may be defined using imperative programming languages, such
as, Javascript, Ruby, Python, Perl, or the like, or combination
thereof. Likewise, in some embodiments, declarative programming,
such as, JSON, XML, may be used to define BOMs and/or BOM
rules.
At decision block 1008, in one or more of the various embodiments,
if the allocation of the activities to the target activity object
may be finished, control may be returned to a calling process;
otherwise, control may loop back to block 1006. In one or more of
the various embodiments, the activity modeling engine may be
arranged to support BOMs that reference one or more BOMs and/or one
or more other activity objects. Accordingly, in some embodiments,
process 1000 may iterate through more than one BOM and/or more the
one activity object to perform an activity allocation. In some
embodiments, the activity modeling engine may be arranged to
recursively iterate through the one or more BOMs during the course
of the activity allocation.
FIG. 11 illustrates a flowchart for process 1100 for providing
activity objects for resource allocation modeling in accordance
with one or one more of the various embodiments. After a start
block, at block 1102, in one or more of the various embodiments, a
service owner may provide one or more specialized activity objects.
In one or more of the various embodiments, an activity modeling
engine may be arranged to provide a user-interface that enables a
user to create specialized activity objects. In some embodiments,
the user-interface may be arranged to enable the user selected one
or more pre-made specialized activity objects. Likewise, in some
embodiments, the user-interface may enable the user to select a
base specialized activity object for further customization. For
example, in one or more of the various embodiments, a user may
elect to create a new service object, project object, department
object, business unit, or the like.
At block 1104, in one or more of the various embodiments, the
service owner may provide a bill-of-material (BOM) for the
specialized activity object. In one or more of the various
embodiments, the user may configure the specialized activity object
according to its purpose. In one or more of the various
embodiments, the user may define a BOM that defines the resources
provided by the object. Also, the user may define the units that
correspond to the produced resources. For example, a BOM define
resource allocation into term of number of items, amount of
storage, required capacity, or the like, or combination thereof.
For example, an BOM may define that resources provided by an IT
department may be allocated in terms of laptop computers, disk
drive storage quotas, service calls, and so on. Accordingly, in
this example, rather than allocating costs of resources in terms of
money (e.g., $1000 per laptop), the IT department may allocate
resources in terms of number of laptops provided.
In one or more of the various embodiments, the price of the
allocated resources may be set equal to their actual cost (pass
through), higher than actual cost, or lower than actual cost. In
some embodiments, setting a price that is lower than actual costs
may reflect an organization policy to promote the user or adoption
of particular resources. Accordingly, resources from another source
may be allocated to the activity object (e.g., IT department) to
offset the reduced price.
At block 1106, in one or more of the various embodiments, the
specialized activity object may be provided for use in modeling
resource allocation using an activity model. In one or more of the
various embodiments, the activity object may be added to a list or
gallery for adding to an activity model.
In some embodiments, the specialized activity object may already be
part on an activity model. Accordingly, the updates to the
specialized activity object may be promulgates through the activity
model. Next, control may be returned to a calling process.
FIG. 12 illustrates a flowchart for process 1200 for using activity
based resource allocation modeling in accordance with one or one
more of the various embodiments. After a start block, at block
1202, in one or more of the various embodiments, provide a resource
allocation plan based on an activity model. In some embodiments,
activity models may be used to plan future/anticipated resource
allocations for an organization.
At block 1204, in one or more of the various embodiments, provide
real-time resource allocation information based on actual usage. In
one or more of the various embodiments, information from external
or internal sources representing actual resource allocation (e.g.,
production and consumption of resources) may be provided to an
activity modeling engine, such as activity modeling engine 324
and/or a resource modeling engine, such as resource modeling engine
322.
At decision block 1206, in one or more of the various embodiments,
if the planned use is different than actual use, control may flow
to block 1208; otherwise, control may be returned to a calling
process. For example, an activity model may show that 1000 laptops
are allocation from the IT department object to other activity
objects. However, in this example, if the actual number of laptops
allocated are 1100, the planned allocations may be determined to be
inaccurate.
At block 1208, in one or more of the various embodiments, modify
the activity model based on the actual usage of resources. In one
or more of the various embodiments, an activity modeling engine may
be arranged to modify one or more activity models in response to
actual allocation information. In some embodiments, the activity
modeling engine may be arranged to automatically modify the
activity model. Also, in some embodiments, the activity modeling
engine may be arranged to notify users if discrepancies between
actual allocations and planned allocations may be discovered.
At decision block 1210, in one or more of the various embodiments,
if the changes to the activity model should be push to an
underlying data model, control may flow to block 1212; otherwise,
control may be returned to a calling process. In one or more of the
various embodiments, activity models may be associated with one or
more underlying data model. Thus, in some embodiments, changes made
to activity models may be propagated to their underlying data
models.
At block 1212, in one or more of the various embodiments, one or
more data models may be updated based on changes made to their
associated with the activity models. For example, if a data model
shows that IT services is allocating $100,000 to Sales. If actual
allocation information shows that IT services provided 800 laptop
computers rather than 1000, the allocation value in the data model
may be reduced to $80,000 (assuming $1000 per laptop computer). In
one or more of the various embodiments, a resource modeling engine
may be arranged to automatically modify the underlying data models
in response discrepancies between planned and actual activity model
allocations. In other cases, the resource modeling engine may be
arranged to notify users of the discrepancies between planned and
actual allocation so they may modify the data model at their
discretion.
It will be understood that each block of the flowchart
illustration, and combinations of blocks in the flowchart
illustration, can be implemented by computer program instructions.
These program instructions may be provided to a processor to
produce a machine, such that the instructions, which execute on the
processor, create means for implementing the actions specified in
the flowchart block or blocks. The computer program instructions
may be executed by a processor to cause a series of operational
steps to be performed by the processor to produce a
computer-implemented process such that the instructions, which
execute on the processor to provide steps for implementing the
actions specified in the flowchart block or blocks. The computer
program instructions may also cause at least some of the
operational steps shown in the blocks of the flowchart to be
performed in parallel. These program instructions may be stored on
some type of machine readable storage media, such as processor
readable non-transitive storage media, or the like. Moreover, some
of the steps may also be performed across more than one processor,
such as might arise in a multi-processor computer system. In
addition, one or more blocks or combinations of blocks in the
flowchart illustration may also be performed concurrently with
other blocks or combinations of blocks, or even in a different
sequence than illustrated without departing from the scope or
spirit of the invention.
Accordingly, blocks of the flowchart illustration support
combinations of means for performing the specified actions,
combinations of steps for performing the specified actions and
program instruction means for performing the specified actions. It
will also be understood that each block of the flowchart
illustration, and combinations of blocks in the flowchart
illustration, can be implemented by special purpose hardware-based
systems, which perform the specified actions or steps, or
combinations of special purpose hardware and computer instructions.
The foregoing example should not be construed as limiting and/or
exhaustive, but rather, an illustrative use case to show an
implementation of at least one of the various embodiments of the
invention.
* * * * *
References